Engineering with Computers

, Volume 25, Issue 1, pp 3–13

Nanoshell-mediated laser surgery simulation for prostate cancer treatment

Authors

    • Computational Bioengineering and Nanotechnology Lab, Department of Mechanical EngineeringThe University of Texas at San Antonio
  • David Fuentes
    • Institute for Computational Engineering and SciencesThe University of Texas at Austin
  • Andrea Hawkins
    • Institute for Computational Engineering and SciencesThe University of Texas at Austin
  • Jon Bass
    • Institute for Computational Engineering and SciencesThe University of Texas at Austin
  • Marissa Nichole Rylander
    • Department of Mechanical Engineering and School of Biomedical Engineering and SciencesVirginia Tech
  • Andrew Elliott
    • Department of Imaging PhysicsThe University of Texas M.D. Anderson Cancer Center
  • Anil Shetty
    • Department of Imaging PhysicsThe University of Texas M.D. Anderson Cancer Center
  • R. Jason Stafford
    • Department of Imaging PhysicsThe University of Texas M.D. Anderson Cancer Center
  • J. Tinsley Oden
    • Institute for Computational Engineering and SciencesThe University of Texas at Austin
Original Article

DOI: 10.1007/s00366-008-0109-y

Cite this article as:
Feng, Y., Fuentes, D., Hawkins, A. et al. Engineering with Computers (2009) 25: 3. doi:10.1007/s00366-008-0109-y

Abstract

Laser surgery, or laser-induced thermal therapy, is a minimally invasive alternative or adjuvant to surgical resection in treating tumors embedded in vital organs with poorly defined boundaries. Its use, however, is limited due to the lack of precise control of heating and slow rate of thermal diffusion in the tissue. Nanoparticles, such as nanoshells, can act as intense heat absorbers when they are injected into tumors. These nanoshells can enhance thermal energy deposition into target regions to improve the ability for destroying larger cancerous tissue volumes with lower thermal doses. The goal of this paper is to present an integrated computer model using a so-called nested-block optimization algorithm to simulate laser surgery and provide transient temperature field predictions. In particular, this algorithm aims to capture changes in optical and thermal properties due to nanoshell inclusion and tissue property variation during laser surgery. Numerical results show that this model is able to characterize variation of tissue properties for laser surgical procedures and predict transient temperature fields comparable to those measured by in vivo magnetic resonance temperature imaging techniques. Note that the computational approach presented in the study is quite general and can be applied to other types of nanoparticle inclusions.

Keywords

Laser-induced thermal therapy Nanoparticles Prostate cancer Laser-tissue interaction Bioheat transfer Finite element method

Copyright information

© Springer-Verlag London Limited 2008